Field capacity is one of the most commonly used, and yet poorly defined, soil hydraulic properties. Traditionally, field capacity has been defined as the amount of soil moisture after excess water has drained away and the rate of downward movement has materially decreased. Unfortunately, this qualitative definition does not lend itself to an unambiguous quantitative approach for estimation. Because of the vagueness in defining what constitutes “drainage of excess water” from a soil, the estimation of field capacity has often been based upon empirical guidelines. These empirical guidelines are either time, pressure, or flux based. In this paper, we developed a numerical approach to estimate field capacity using a flux‐based definition. The resulting approach was implemented on the soil parameter data set used by Schaap et al. (2001), and the estimated field capacity was compared to traditional definitions of field capacity. The developed modeling approach was implemented using the HYDRUS‐1D software with the capability of simultaneously estimating field capacity for multiple soils with soil hydraulic parameter data. The Richards equation was used in conjunction with the van Genuchten‐Mualem model to simulate variably saturated flow in a soil. Using the modeling approach to estimate field capacity also resulted in additional information such as (1) the pressure head, at which field capacity is attained, and (2) the drainage time needed to reach field capacity from saturated conditions under nonevaporative conditions. We analyzed the applicability of the modeling‐based approach to estimate field capacity on real‐world soils data. We also used the developed method to create contour diagrams showing the variation of field capacity with texture. It was found that using benchmark pressure heads to estimate field capacity from the retention curve leads to inaccurate results. Finally, a simple analytical equation was developed to predict field capacity from soil hydraulic parameter information. The analytical equation was found to be effective in its ability to predict field capacities.

[1] A recently introduced measurement approach allows in situ determination of subsurface soil water evaporation by means of heat-pulse probes (HPP). The latent heat component of subsurface evaporation is estimated from the residual of the sensible heat balance. This heat balance method requires measurement of vertical soil temperature and estimates of thermal properties for soil water evaporation determination. Our objective was to employ numerically simulated thermal and hydraulic processes using constant or diurnally cycled surface boundary conditions to evaluate and understand this technique. Three observation grid spacings, namely, 6 mm (tri-needle HPP), 3 mm (penta-needle HPP) and 1 mm, along with three soil textures (sand, silt, and silty clay) were used to test the heat balance method. The comparison of heat balance -based evaporation rate estimates with an independent soil profile water balance revealed substantial errors when thermal conductivity ðÞ was averaged spatially across the evaporation front. Since the conduction component of heat flux is the dominant process at the evaporation front, the estimation of evaporation rate was significantly improved using depth-dependent instead of a space-averaged . A nearsurface ''undetectable zone'' exists, where the heat balance calculation is irreconcilable, resulting in underestimation of total subsurface evaporation. The method performs better for medium-and coarse-textured soils than for fine-textured soils, where portions of the drying front may be maintained longer within the undetectable zone. Using smaller temperature sensor spacing near the soil surface minimized underestimation from the undetectable zone and improved accuracy of total subsurface evaporation rate estimates.

The diffusion of warm, humid air into an initially cold, dry, sandy column was analyzed to study the movement of water vapor and liquid water under nonisothermal and low water content conditions. The analysis was performed using the HYDRUS‐1D code. While the water retention curve of sand was measured experimentally, the unsaturated hydraulic conductivity function was inversely estimated from the observed water content profiles in the column. The estimated unsaturated hydraulic conductivity function displayed a shape that reflected distinct processes of capillary pore water flow and film flow at high and low water contents, respectively. Four components of the total water flux, including thermal and isothermal liquid water and water vapor fluxes, were evaluated using the calibrated soil hydraulic properties. Evaporation and condensation rates were calculated based on water mass balance. Water vapor entered the soil column at the hot surface and condensed at the cold bottom. Subsequently, liquid water moved upward and evaporated at the moisture front in the middle of the column where the relative humidity decreased below unity. Liquid water and water vapor then circulated between the bottom and the moisture front, accompanied by condensation and evaporation processes. The impact of the enhancement factor in the thermal vapor diffusion term could not be clearly identified from available experimental water content profiles. Increases in liquid water flow and the evaporation rate could be compensated for by increases in vapor flow and the condensation rate. Additional data would be needed to fully evaluate the effect of the enhancement factor.

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The mechanistic study of the initial step in direct arylation provides valuable insight for optimising reaction conditions.